Triple

T33544838
Position Surface form Disambiguated ID Type / Status
Subject A14 motorway (Germany) E859174 entity
Predicate hasJunctionWith P1018 FINISHED
Object A20 motorway (Germany)
The A20 motorway in Germany is a major east–west autobahn in northern Germany, often called the "Baltic Sea motorway," connecting key ports and cities along the Baltic coast.
E2078426 NE FINISHED

How this triple was built (2 steps)

Every LLM step that produced this triple, in pipeline order — named-entity classification, the disambiguation choices (the exact options shown, with the pick highlighted), and the generated description. The batch + timestamp of each is in the Provenance table below.

NER Named-entity recognition gpt-5-mini
Instruction
Given a phrase, classify it is english named entity (e.g., persons, organizations, works of art) in Latin script, or not (e.g., literals, dates, URLs, verbose phrases). For disambiguation, the statement where the phrase occurs as object is also given. Please return a JSON object with `phrase` (string, the phrase being analyzed) and `is_ne` (boolean, indicating whether the phrase is a Named Entity).
Input
Phrase: A20 motorway (Germany) | Statement: [A14 motorway (Germany), hasJunctionWith, A20 motorway (Germany)]
NEDg Description generation gpt-5.1
Instruction
Generate a one-sentence description of the target entity. 
You are given a context triple in the form (subject, predicate, object), where the object is the target entity. 
# Instructions
Use the triple to infer relevant information about the entity. Describe the entity based on what is most defining, well-known. 
Avoid repeating the information from the triple, unless really essential.
# Response Format
Return only the sentence: "Description: [one-sentence description of the target entity]"
Input
Entity: A20 motorway (Germany)
Triple: [A14 motorway (Germany), hasJunctionWith, A20 motorway (Germany)]
Generated description
The A20 motorway in Germany is a major east–west autobahn in northern Germany, often called the "Baltic Sea motorway," connecting key ports and cities along the Baltic coast.

Provenance (5 batches)

The batch behind each pipeline step, in order, with when it ran. Timestamps are batch-level — stages were processed in waves, so the object chain (NER → NED1 → NEDg → NED2) reads in order, but predicate / elicitation batches can sit in a different wave.

Step Stage Batch ID Status When
creating Elicitation batch_69f3497a5be08190a39b12736899e034 completed April 30, 2026, 12:22 p.m.
NER Named-entity recognition batch_69f6f6e508788190a4f66e92f6a580e5 completed May 3, 2026, 7:19 a.m.
NED1 Entity disambiguation (via context triple) batch_6a36a00f5cd88190a5aef8c90dcaaf59 completed June 20, 2026, 2:13 p.m.
NEDg Description generation batch_6a36a13fe784819098157b852512d1a8 completed June 20, 2026, 2:18 p.m.
NED2 Entity disambiguation (via description) batch_6a36a1c4630c819081b1afb23720f027 completed June 20, 2026, 2:20 p.m.
Created at: May 1, 2026, 1:39 a.m.